There is now extensive interest in reasoning about moving objects. A PST knowledge base is a set of PST-atoms which are statements of the form "Object o is/was/will be at location L at time t with probability in the interval [L,U]". In this paper, we study mechanisms for belief revision in PST-KBs. We propose multiple methods for revising PST-KBs. These methods involve finding maximally consistent subsets, as well as changing the spatial, temporal, and probabilistic components of the atoms. We show that some methods cannot satisfy the AGM axioms for belief revision, while others do but are coNP-hard. Finally we present an algorithm for revision through probability change which runs in polynomial time and satisfies the AGM axioms.